Correlation of the absorption coefficient with a reduction in mean mass for dissolved organic matter in southwest Florida river plumes

Results are presented from an investigation of the relationship between molecular mass distribution and optical properties for colored dissolved organic matter (CDOM); a complex assembly of organic macromolecules of marine and freshwater origin found throughout the surface ocean. Unique data are derived from the application of a new technique, a combination of a hydrophilic–lipophilic copolymer-based solid phase extraction (SPE) with electrospray ionization (ESI) continuous flowing ion trap mass spectrometry (cf-MS), for the direct determination of CDOM mass distribution. An evaluation of this copolymer-based extraction technique for the analysis of Suwannee River Natural Organic Matter (SRNOM) reference material revealed that the current method compares favorably with C₁₈ modified silica or XAD resin-based extraction methods reported in the literature when considering extraction efficiency or low extraction bias for CDOM. The mass distribution of CDOM in several freshwater to marine transition zones along coastal southwestern Florida has been determined with this technique. All rivers in the study region had a bimodal distribution of masses. A case study of the Caloosahatchee River outflow CDOM mass distribution data are presented as an example of the modification in mass distributions. The lower mass mode of the bimodal distribution was observed to have a relatively stable mean throughout the study region at 406±9 Da, while decreasing in concentration in a non-conservative manner with salinity. In contrast, the upper mass mode of the bimodal distribution was observed to have a variable mean, reaching 1408 Da in the least saline waters and decreasing by 174 Da through the transect toward higher salinity coastal waters. Coinciding with this reduction in mean mass for the upper distribution is a non-conservative reduction in concentration when compared with salinity. We define apparent organic carbon (AOC) as a function of the cf-MS determined total integrated area and use this value to determine concentration of the total extracted CDOM. Unique correlations between the CDOM fluorescence (350-nm excitation/450-nm emission) and the AOC for these coastal samples have been observed for each of three rivers in the study region. The steepest slope and highest correlation between optical and mass spectral properties are observed in rivers with strongly absorbing waters originating in the Florida Everglades and lowest in rivers draining clearer waters from widely variable and anthropogenic influenced regions. The trends in molecular mass distribution and corresponding optical properties support the theory that CDOM in coastal zones is environmentally processed material from terrestrial sources. Probable cause of the reduction in mean mass and suggestions for further investigation of sources and transformations of CDOM are discussed.     

Solvent extraction of copper acetylacetonate in studies of copper(II) speciation in seawater

A liquid-liquid partition, ligand exchange procedure involving the formation of copper(II) complexes with acetylacetone is presented for the determination of stability constants and concentrations of copper chelators in seawater. Acetylacetone competes with natural ligands for copper, and the equilibrium concentration of the copper acetylacetonate complex is used in speciation calculations. The concentration of the complex is calculated by partitioning a fraction of it into an organic phase and determining the total Cu concentration in that phase by back extracting with acid, and analyzing by flameless atomic absorption spectroscopy. The concentration of Cu acetylacetonate in seawater in equilibrium with the organic phase is calculated from the partition coefficient. The simple, thermodynamically well characterized procedure offers several advantages over previous techniques. Studies using organic free seawater and model ligands show good agreement between experimental and calculated conditional stability constants. Studies from seawater in Biscayne Bay, Florida, indicate two ligand types are present; type 1, K₁ = 1.2 × 10¹², C_L1 = 5.1 × 10⁻⁹ M; type 2, K₂ = 2.8 × 10¹⁰, C_L2 = 1.1 × 10⁻⁷ M. Speciation is dominated by ligand type 1. Depth profiles of [Cu(II)]_free/[Cu(II)]_total measured with the procedure at ambient copper concentrations show an increase from < 5 × 10⁻⁵ at 50–60 m to > 1 × 10⁻³ at the surface at two stations off the Florida coast.     

Luminescence quenching of dissolved organic matter in seawater

To characterize more fully the nature of the fluorophores present in the dissolved organic matter found in seawater, steady state and time-resolved measurements of the luminescence quenching of a number of samples of marine dissolved organic matter with known quenchers, such as iodide, acrylamide and methyl viologen (MV) (1,1′-dimethyl-4,4′-bipyridinium), were compared. Quenching characteristics of these systems were analyzed using Stern-Volmer plots for both intensity and lifetime measurements. The bimolecular quenching constants, κ_q, for these quenchers were found to decrease in the order MV²⁺ (κ_q 10¹⁰M⁻¹s⁻¹) > I⁻ (κ_q 2 × 10⁹ M⁻¹ s⁻¹) >CH₂CHCONH₂ (κ_q 2 × 10⁸ M⁻¹ s⁻¹) for the samples measured. The results also show that different samples are quenched to differing extents by the quenchers studied, that ionic strength alters the quenching constants, and that both static and diffusional quenching mechanisms may operate.Such studies are appropriate to the quantification of the reactivity of the singlet states of the chromophores found within marine dissolved organic matter. Although excess energy of the singlet state may be readily transferred to another chemical species, the combination of competing physical deactivation paths and the low concentrations of efficient quenches in the oceans serves to lessen the direct chemical impact of this process.     

Review of nekton patterns and ecological processes in seagrass landscapes

We reviewed seagrass landscape studies on nekton (fish and larger mobile crustaceans) to summarise: (1) patterns of nekton abundance in relation to patch attributes; and (2) models used to explain processes underpinning observed patterns. The response of nekton to landscape attributes is highly variable. Different taxa showed increasing densities with: increasing and decreasing patch size (12 and 11 taxa, respectively), increasing and decreasing proximity within a patch to edge (9, 14), increasing and decreasing distances from nearest seagrass patch (4, 11), and with patches perpendicular and parallel to currents (1, 2). The majority of taxa (213 out of 281, or 82%) showed no relationships. Landscape scale patterns are important for some species but evidence so far does not demonstrate major landscape effects overall. The lack of pattern might reflect the overriding importance of other factors such as within-patch characteristics, water depth or position within an estuary. It might also result from measurements at the wrong scale. The rigour of surveys can be improved by avoiding confounding of patch attributes by other factors, increasing awareness of statistical power, and more considered survey designs for attributes such as edge effects. The predation model is the most frequently invoked and tested model. Other explanatory models are based on disturbance, rates of encounter, food availability, larval supply, migration and reproductive success, but in many cases are not based on observed patterns. The best experimental work has been done on nekton species for which landscape studies have been built on a detailed understanding of the ecology of the species, such as for blue crabs (Callinectes sapidus). As this basic ecological platform is laid for more species, the landscape approach will become increasingly fruitful.     

Modeling spatial dependence in high spatial resolution hyperspectral data sets

 As either the spatial resolution or the spatial scale for a geographic landscape increases, both latent spatial dependence and spatial heterogeneity also will tend to increase. In addition, the amount of georeferenced data that results becomes massively large. These features of high spatial resolution hyperspectral data present several impediments to conducting a spatial statistical analysis of such data. Foremost is the requirement of popular spatial autoregressive models to compute eigenvalues for a row-standardized geographic weights matrix that depicts the geographic configuration of an image's pixels. A second drawback arises from a need to account for increased spatial heterogeneity. And a third concern stems from the usefulness of marrying geostatistical and spatial autoregressive models in order to employ their combined power in a spatial analysis. Research reported in this paper addresses all three of these topics, proposing successful ways to prevent them from hindering a spatial statistical analysis. For illustrative purposes, the proposed techniques are employed in a spatial analysis of a high spatial resolution hyperspectral image collected during research on riparian habitats in the Yellowstone ecosystem. Received: 25 February 2001 / Accepted: 2 August 2001     

Displacement‐based seismic analysis for out‐of‐plane bending of unreinforced masonry walls

This paper addresses the problem of assessing the seismic resistance of brick masonry walls subject to out‐of‐plane bending. A simplified linearized displacement‐based procedure is presented along with recommendations for the selection of an appropriate substitute structure in order to provide the most representative analytical results. A trilinear relationship is used to characterize the real nonlinear force–displacement relationship for unreinforced brick masonry walls. Predictions of the magnitude of support motion required to cause flexural failure of masonry walls using the linearized displacement‐based procedure and quasi‐static analysis procedures are compared with the results of experiments and non‐linear time‐history analyses. The displacement‐based procedure is shown to give significantly better predictions than the force‐based method. Copyright © 2002 John Wiley & Sons, Ltd.     

Spatial and temporal variations of hydrogen peroxide in Gulf of Mexico waters

Hydrogen peroxide concentrations in the Gulf of Mexico were measured on two cruises in May and August, 1982, in a variety of locations ranging from oligotrophic oceanic stations to highly productive coastal sites. Measurements were made using a fluorescence decay technique. Depth profiles of H₂O₂ exhibit surface maxima of 1?2 × 10^?7 mol L^?1 and decreasing concentrations with depth. Peroxide concentrations decreased only slightly or were invariant with depth in the mixed layer but decreased sharply to below the limit of detection (5 × 10^?9 mol L^?1) in the region of the pycnocline at the base of the mixed layer. Surface concentrations were generally highest in coastal regions but did not vary by more than a factor of three among all stations studied. There was a marked diel variation in peroxide profiles, with the highest values occurring during the late afternoon, and the lowest values occurring at dawn. Diel variations were more pronounced in coastal surface waters than in oligotrophic waters. The observations are consistent with photochemical formation of H₂O₂ by photooxidation of dissolved organic matter. However, other formation pathways, such as biological formation or atmospheric deposition, cannot be ruled out at this point.     

A Spatial Filtering Specification for an Auto-negative Binomial Model of Anopheles arabiensis Aquatic Habitats

This research accounts for spatial autocorrelation by including latent map pattern components as predictor variables in a malaria mosquito aquatic habitat model specification. The data used to derive the model was from a digitized grid-based algorithm, generated in an ArcInfo database, using QuickBird visible and near-infrared (NIR) data. The Feature Extraction (FX) Module in ENVI 4.4^® was used to categorize individual pixels of field sampled aquatic habitats into separate spectral classes, convert remotely sensed raster layers to vector coverages, and classify output layers to vector format as ESRI shapefiles. These data were used to construct a geographic weights matrix for evaluation of field and remote sampled covariates of Anopheles arabiensis aquatic habitats, a major vector of malaria in East Africa. The principal finding is that synthetic map pattern variables, which are eigenvectors computed for a geographic weights matrix, furnish an alternative way of capturing spatial dependency effects in the mean response term of a regression model. The spatial autocorrelation components suggest the presence of roughly 11 to 28% redundant information in the aquatic habitat larval count samples. The presence of redundant information in the models suggest that the sampling configuration of the An. arabiensis aquatic habitats, in the study sites, may cause field and remote observations of aquatic habitats to be dependent, rather than independent, moving data analysis away from the classical statistical independence model. A Poisson regression model, with a non-constant, gamma-distributed mean, can decompose field and remote sampled An. arabiensis data into positive and negative spatial autocorrelation eigenvectors, which can assess the precision of a malaria mosquito aquatic habitat map and the significance of all factors associated with larval abundance and distribution in a riceland agroecosystem.